DIGITALNA ARHIVA ŠUMARSKOG LISTA
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 ŠUMARSKI LIST 11-12/2016 str. 39     <-- 39 -->        PDF weighted using a portable scale. Three live branches, one from the lowest part of the crown, one in the middle and one at the top of the crown were randomly selected. The length and dbh of each selected branches then were measured and weighted.  The needles of each selected branches were removed and weighted. The 5-cm wood disks, selected branches and needles were taken to the labs and air dried for further wood density and carbon analysis. The air dried samples were then oven dried at 105 °C for 24 hours. The total dry biomass of the sampled tree was calculated using the following equation:                 DWi = FWi ´ dwsi / fwsi         Eq.1 Where; DWi is the dry-weight of each tree component (stems, branches and needles), FWi is the total fresh weight of each component, fwsi is fresh weight of the sample, and dwsi denotes dry weight of the sample, respectively. The i represents each tree component, stems, branches and needles, respectively. Statistical analysis – Statistička analiza There were two kinds of equations (univariate and multivariate) for estimating the above-ground tree component biomass (Nordman et al., 2005). The univariate allometric equations are based on the diameter at breast height. On the other hand, multivariate equations use tree height, tree crown length and tree crown width in addition to dbh to estimate the above-ground tree biomass. In practice, the measurement of dbh and tree height are much easier and less time consuming than measuring tree height, crown length, crown width, and dbh all together.  Because of that the allometric equations based on dbh and tree height were chosen (Table 1). Using dbh and tree height, 12 different allometric equations (Table 1) were tested for the prediction of the above-ground biomass of Calabrian pine. These allometric equations were used for the stem, branches and needles separately. The allometric equations presented in this study then were fitted using linear and nonlinear regression analysis. Model Evaluation – Evaluacija modela To select the best models for each tree components of the above-ground biomass, the following criteria were utilized using SPSS statistical software package: a) coefficient of determination (R2), b) residual standard error (RSE), and c) p values of estimated parameters. The selected models were sorted in descending order based on R2 and given a highest rank score for the highest R2 model. The models were